State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, People's Republic of China.
State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, People's Republic of China
Br J Ophthalmol. 2024 Aug 22;108(9):1269-1274. doi: 10.1136/bjo-2023-323171.
To establish and evaluate predictive models for glaucoma-related adverse events (GRAEs) following secondary intraocular lens (IOL) implantation in paediatric eyes.
205 children (356 aphakic eyes) receiving secondary IOL implantation at Zhongshan Ophthalmic Center with a 3-year follow-up were enrolled. Cox proportional hazard model was used to identify predictors of GRAEs and developed nomograms. Model performance was evaluated with time-dependent receiver operating characteristic (ROC) curves, decision curve analysis, Kaplan-Meier curves and validated internally through C-statistics and calibration plot of the bootstrap samples.
Older age at secondary IOL implantation (HR=1.5, 95% CI: 1.03 to 2.19), transient intraocular hypertension (HR=9.06, 95% CI: 2.97 to 27.67) and ciliary sulcus implantation (HR=14.55, 95% CI: 2.11 to 100.57) were identified as risk factors for GRAEs (all p<0.05). Two nomograms were established. At postoperatively 1, 2 and 3 years, model 1 achieved area under the ROC curves (AUCs) of 0.747 (95% CI: 0.776 to 0.935), 0.765 (95% CI: 0.804 to 0.936) and 0.748 (95% CI: 0.736 to 0.918), and the AUCs of model 2 were 0.881 (95% CI: 0.836 to 0.926), 0.895 (95% CI: 0.852 to 0.938) and 0.848 (95% CI: 0.752 to 0.945). Both models demonstrated fine clinical net benefit and performance in the interval validation. The Kaplan-Meier curves showing two distinct risk groups were well discriminated and robust in both models. An online risk calculator was constructed.
Two nomograms could sensitively and accurately identify children at high risk of GRAEs after secondary IOL implantation to help early identification and timely intervention.
建立并评估儿童眼内二次人工晶状体(IOL)植入术后青光眼相关不良事件(GRAE)的预测模型。
共纳入 205 名(356 只患眼)在中山眼科中心接受二次 IOL 植入并随访 3 年的儿童患者。采用 Cox 比例风险模型确定 GRAE 的预测因素并建立列线图。通过时间依赖性接受者操作特征(ROC)曲线、决策曲线分析、Kaplan-Meier 曲线和内部验证的 C 统计量和 Bootstrap 样本的校准图来评估模型性能。
二次 IOL 植入时年龄较大(HR=1.5,95%CI:1.03 至 2.19)、一过性眼内高压(HR=9.06,95%CI:2.97 至 27.67)和睫状沟植入(HR=14.55,95%CI:2.11 至 100.57)被确定为 GRAE 的危险因素(均 P<0.05)。建立了两个列线图。术后 1、2 和 3 年,模型 1 的 ROC 曲线下面积(AUC)分别为 0.747(95%CI:0.776 至 0.935)、0.765(95%CI:0.804 至 0.936)和 0.748(95%CI:0.736 至 0.918),模型 2 的 AUC 分别为 0.881(95%CI:0.836 至 0.926)、0.895(95%CI:0.852 至 0.938)和 0.848(95%CI:0.752 至 0.945)。两个模型在间隔验证中均显示出良好的临床净获益和性能。Kaplan-Meier 曲线显示两个明显的风险组在两个模型中都得到了很好的区分和验证。构建了一个在线风险计算器。
两个列线图可以敏感、准确地识别出儿童眼内二次 IOL 植入术后发生 GRAE 的高危人群,有助于早期识别和及时干预。